Design and Development of Microstructured Optical Fibre Pressure Sensor

Abstract

Pressure sensing at high temperatures is a challenging but vital task for many harsh environment applications in industries such as aerospace, chemical plants, and energy. In this context, this thesis focuses on the design and development of specialty optical fibre sensors, targeted towards high-temperature industrial applications for ensuring efficient operation, enhanced safety, and quality control. The use of single-material fibre sensors allows hightemperature operation by avoiding dopant diffusion. Temperature-compensated single point and multipoint pressure measurements are demonstrated at temperatures up to 900°C using a multimode interferometric technique. Numerical studies are presented and compared with experimental findings. The study is extended to achieve relatively simple and cost-effective pressure measurement using a fibre specklegram sensing technique. Two machine learning algorithms, an instance-based learning model and a deep learning model, are applied to overcome the challenges of specklegram sensing such as dynamic range limitation and crosstalk due to unwanted environmental perturbations. The demonstrated techniques facilitate the development of full-range fibre specklegram sensors and eliminate the need for controlled environments to shield unwanted perturbations, which can often be difficult to achieve. The proposed techniques for fibre specklegram sensing can also be useful for sensing other measurands beyond pressure. The outcomes of this thesis pave the way for the development of stable, reliable, and cost-effective pressure sensors for high-temperature industrial applications. The insights gained from this research provide valuable guidance for optimizing sensor design and material selection, enhancing pressure sensitivity and overall sensor performance.